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All Journal Jurnal Riset Informatika Jurnal Minfo Polgan (JMP)
Prama Natio Adha
Universitas Sulawesi Barat
Computer Science & IT Library & Information Science Mathematics Social Sciences

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Perancangan Sistem Informasi Pengarsipan Surat Berbasis Web pada Kantor Kecamatan Jambi Luar Kota Muaro Jambi Prama Natio Adha; Dian Megah Sari; Irfan AP; Adam Tanniewa; Indra Indra; Abdilla Nurul Azisah Mn; Andi Heriani; Asrul Asrul
Jurnal Minfo Polgan Vol. 14 No. 2 (2025): Artikel Penelitian
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/jmp.v14i2.15698

Abstract

Kantor Kecamatan adalah suatu kantor yang terletak di Pijoan, Jambi Luar Kota Kabupaten Muaro Jambi. Dalam pengolahan data arsip serta penyediaan laporan pada Kantor Kecataman Jambi Luar Kota masih dilakukan dengan mencatat data dalam formulir dan merekap serta menyimpan berkas pada rak atau lemari berkas. Tujuan penelitian ini adalah untuk menganalisa sistem yang sedang berjalan, agar dapat mengatasi masalah-masalah yang dihadapi pada pada Kantor Kecamatan Jambi Luar Kota Muaro Jambi, dengan cara merancang Perancangan Sistem Informasi Pengarsipan Surat Berbasis Web Pada Kantor Kecamatan Jambi Luar Kota Muaro Jambi. Kerangka Kerja Penelitian yang akan dilakukan dalam penyelesaian masalah yang dibahas yaitu, melakukan identifikasi, melakukan pencarian informasi berdasarkan landasan- landasan teori, pengumpulan data dengan metode observasi dan wawancara, menganalisis untuk mencari solusi atas permasalahan yang didhadapi Kantor Kecamatan Jambi Luar Kota Muaro Jambi. Metode Pengembangan sistem menggunakan model air terjun (waterfall), implementasi penelitian ini menggunakan Bahasa Perograman PHP dan DBMS MySQL. Hingga menghasilkan aplikasi pengolahan data yang di harapkan dapat mempermudah dalam pengolahan data maupun pembuatan laporan.
COMPARATIVE PERFORMANCE OF EFFICIENTNET-B0 AND RESNET-50 FOR MELANOMA DETECTION IN DERMOSCOPY IMAGES Nourman Irjanto; Hamdy Nur Saidy; Prama Natio Adha
Jurnal Riset Informatika Vol. 8 No. 3 (2026): Juni 2026
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v8i3.527

Abstract

Melanoma is the most aggressive form of skin cancer with high metastatic potential, and early detection is crucial for improving patient survival. Although deep learning models such as ResNet-50 and EfficientNet-B0 have shown promising results in melanoma classification, systematic comparisons using identical experimental protocols remain limited. This study aims to comprehensively compare the performance of EfficientNet-B0 and ResNet-50 in detecting melanoma from dermoscopy images across multiple evaluation dimensions, including accuracy, precision, recall, F1-score, and computational efficiency. A quantitative experimental research design was employed using the publicly available HAM10000 dataset, consisting of 10,015 dermoscopy images categorized into melanoma and non-melanoma classes. Both models were implemented using transfer learning with ImageNet pretrained weights, trained under identical conditions including data augmentation, class imbalance handling using weighted loss, and standardized hyperparameters. Results showed that EfficientNet-B0 achieved superior performance with 91.5% accuracy, 89.8% precision, 88.2% recall, and 89.0% F1-score, compared to ResNet-50 which achieved 89.2% accuracy, 87.5% precision, 85.3% recall, and 86.4% F1-score. Furthermore, EfficientNet-B0 demonstrated significant computational advantages with only 5.3 million parameters (79% fewer than ResNet-50’s 25.6 million). In conclusion, EfficientNet-B0 outperforms ResNet-50 in both accuracy and computational efficiency, making it more suitable for deployment in resource-constrained clinical environments such as mobile telemedicine applications.
Co-Authors Abdilla Nurul Azisah Mn Adam Tanniewa Andi Heriani Asrul Asrul Dian Megah Sari Hamdy Nur Saidy Indra Irfan AP Nourman Irjanto